D. Tien Bui

Management, Monitoring, Policy and Law · 2012–2020

A researcher in the Science corpus: 30 papers; trusts 57 researchers and is trusted by 45 researchers here, as inferred from the citation graph.

Subfields

• Management, Monitoring, Policy and Law — 174 citations into it; #73 of 2,821 by trust here, #23 by citations
• Global and Planetary Change — 151 citations into it; #363 of 10,225 by trust here, #298 by citations
• Artificial Intelligence — 105 citations into it; #25,816 of 35,345 by trust here, #12,387 by citations
• Safety, Risk, Reliability and Quality — 84 citations into it; #214 of 1,220 by trust here, #27 by citations
• Mechanical Engineering — 76 citations into it; #941 of 8,300 by trust here, #1,481 by citations
• Environmental Engineering — 52 citations into it; #2,865 of 5,479 by trust here, #707 by citations
• Statistics and Probability — 42 citations into it
• Computer Vision and Pattern Recognition — 40 citations into it

Whom D. Tien Bui trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Biswajeet Pradhan
2. Saro Lee
3. Isik Yilmaz
4. Vladimir Naumovich Vapni
5. J. Ross Quinlan
6. Vladimir Naumovich Vapnik
7. Leo Breiman
8. Haoyuan Hong
9. Hamid Reza Pourghasemi
10. Wei Chen

Who trusts D. Tien Bui overall

1. Binh Thai Pham
2. Hamid Reza Pourghasemi
3. Biswajeet Pradhan
4. Wei Chen
5. Khabat Khosravi
6. Himan Shahabi
7. Ataollah Shirzadi
8. Indra Prakash
9. Kamran Chapi
10. E. Kutlug Sahin

Papers from D. Tien Bui's perspective

Ordered by how strongly the researchers D. Tien Bui trusts endorse each paper. Same corpus, a different order for every researcher.

1. The Nature of Statistical Learning Theory
2. Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran (Proceedings of the Indian Academy of Sciences, Earth and Planetary Sciences)
3. Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy
4. Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression (Landslides)
5. Landslide susceptibility mapping : A comparison of logistic regression and neural networks methods in a medium scale study, Hendek Region (Turkey)
6. Determination and application of the weights for landslide susceptibility mapping using an artificial neural network
7. Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China. (Science of the Total Environment)
8. An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps
9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
10. Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkey) by fuzzy approach

Their papers

• The feasibility of Levenberg–Marquardt algorithm combined with imperialist competitive computational method predicting drag reduction in crude oil pipelines (2020) — 59 citations
• A Hybrid Intelligence Approach to Enhance the Prediction Accuracy of Local Scour Depth at Complex Bridge Piers (2020) — 84 citations
• Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance (2020) — 1,018 citations
• The effect of sample size on different machine learning models for groundwater potential mapping in mountain bedrock aquifers (2020) — 120 citations
• Herding Behaviors of grasshopper and Harris hawk for hybridizing the neural network in predicting the soil compression coefficient (2020) — 70 citations
• A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area. (2019) — 361 citations
• Remote Sensing Approaches for Monitoring Mangrove Species, Structure, and Biomass: Opportunities and Challenges (2019) — 301 citations
• A novel artificial intelligence approach based on Multi-layer Perceptron Neural Network and Biogeography-based Optimization for predicting coefficient of consolidation of soil (2019) — 180 citations
• New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed (2019) — 114 citations
• Intelligent Prediction of Blasting-Induced Ground Vibration Using ANFIS Optimized by GA and PSO (2019) — 119 citations
• Landslide susceptibility modelling using different advanced decision trees methods (2018) — 59 citations
• GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method (2018) — 257 citations
• A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran. (2018) — 676 citations
• Landslide susceptibility assessment at the Wuning area, China: a comparison between multi-criteria decision making, bivariate statistical and machine learning methods (2018) — 121 citations
• Spatial prediction of groundwater spring potential mapping based on an adaptive neuro-fuzzy inference system and metaheuristic optimization (2018) — 158 citations
• Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China) (2018) — 449 citations
• Spatial Prediction of Rainfall-Induced Landslides Using Aggregating One-Dependence Estimators Classifier (2018) — 97 citations
• A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility (2017) — 836 citations
• A novel hybrid artificial intelligence approach for flood susceptibility assessment (2017) — 561 citations
• Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS (2017) — 577 citations